Our thinking, perception, and ability to understand language are processed in the outermost layer of the brain, the cerebral cortex. Knowing exactly where our senses and perceptions take shape in the brain is important for unraveling how aging, neurological conditions, and psychiatric illnesses affect our health. Scientists have used a variety of techniques to map the brain’s organization over the past century, from examining tissue under a microscope to sophisticated brain imaging methods. However, these measures don’t always reveal the same boundaries and borders in the brain’s landscape.

To get a more holistic view of how the cortex is organized, a team led by Drs. Matthew Glasser and David Van Essen at Washington University in St. Louis combined several measures to create one cohesive brain map. The team collected high quality magnetic resonance imaging (MRI) data from 130 female and 80 male participants of the Human Connectome Project (HCP). The study was funded by the NIH Blueprint for Neuroscience Research. Results were published in Nature on July 20, 2016.

The researchers measured both structural and functional properties of the participants’ brains. Structural MRI scans revealed the thickness of the cortex and the amount of protective sheathing, or myelin, surrounding brain cells. Functional MRIs measured the participants’ brain activity during a resting state and while performing different tasks, such as listening to a story, looking at pictures, or doing math. The scientists used the data to help distinguish brain regions by their specialized roles and determine which regions’ activities were correlated—their “functional connectivity.”

The researchers use a semi-automated approach to combine the data from these multiple measures, focusing on where at least 2 measures changed together across the cortical surface. This approach mapped 180 distinct areas within each half of the cortex—confirming 83 previously known subdivisions and identifying 97 new areas.

Next, the team verified that the brain map created from the averaged data set could be applied to new data. They trained a machine learning classifier to recognize the “fingerprint” of each cortical area. Then they applied the algorithm to 210 additional HCP participants’ brain scans. The classifier found nearly 97% of all 180 brain areas across all 210 subjects. In a few cases, participants’ brain regions weren’t in typical places; however, the data-derived algorithms were still able to successfully identify and map them. As better data are collected with improved neuroimaging methods, the researchers note, some brain regions may turn out to have further subdivisions or be subunits of other areas.

“These new insights and tools should help to explain how our cortex evolved and the roles of its specialized areas in health and disease, and could eventually hold promise for unprecedented precision in brain surgery and clinical work-ups,” says Dr. Bruce Cuthbert, acting director of NIH’s National Institute of Mental Health (NIMH).